By Topic

Causal knowledge elicitation based on elicitation failures

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Mussi, S. ; CILEA, Italy

The paper presents an approach to causal knowledge elicitation supported by a tool directly used by the domain expert. This knowledge elicitation approach is characterized by trying to guess an interpretation of the knowledge entered by the expert. The tool (initially general), as it is used, self customizes its guessing capability, remembers failures in guessing (in order to avoid similar failures in the future) and when they occur elicits their explanations. Even in this case, elicitation is supported by guessing on the basis of previous similar failures. The resulting overall effect is that the tool digs up tenaciously causal knowledge from the expert's mind, playing in this way a cooperative role for model building

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:7 ,  Issue: 5 )